[R] normality testing with nortest

[Rolf Turner]

I don't know from the nortest package, but it should ***always***
be the case that you test hypotheses

	H_0:  The data have a normal distribution.
vs.
	H_a:  The data do not have a normal distribution.

So if you get a p-value < 0.05 you can say that

		***there is evidence***

(at the 0.05 significance level) that the data are not from a
normal distribution.

If the nortest package does it differently (and I don't really see
how it possibly could!) then it is confusingly designed.  I rather
suspect that its design is just fine, and that it does what it should
do.

				cheers,

					Rolf Turner
					rolf at math.unb.ca

Original message:

>  	I have a question regarding normality testing with the nortest 
> package.  I have to admit, my question is so general that it might more be 
> suited a newsgroup such as sci.math.  However, just in case it is 
> implemented differently, I was hoping someone who has used it can help me 
> out.
> 
>  	I just want to double check that for all of the tests, the null 
> hypothesis is whether or not the input distribution *differs* with the 
> normal distribution.  So, if you get a p-value less than (say) 0.05, you 
> can reject the null hypothesis at a 95% confidence level and say that the 
> input distribution is *not* normal.
> 
>  	So these tests check/confirm whether a distribution is not 
> normal...as opposed to confirming that it is normal.  Does this sound 
> about right?
> 
> Ray